Evaluation of the Australian Wage Subsidy Special Youth ...

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7.2.2 Propensity score matching and the effect of reduced specification
Augurzky and Schmidt (2001) argue that although all available variables that rule the
selection process are usually included in the participation equation, it may be better to
remove variables of lesser importance from the specification. Their analysis showed that
only including variables that were strongly significant could help combat the unnecessary
effort of trying to balance these variables, which they found came at the expense of
balance of the most relevant variables. In light of this, variables with low significance, or
with only a theoretically minor role in employment, are candidates for exclusion from the
probit for participation. Heckman, Ichimura and Todd (1997) also suggest that it is useful
to compare the matching results from a reduced model of participation to that of the fuller
model, in order to better assess the different approach to modelling entailed.
In light of this a reduced specification of the probit for the propensity is proposed. The
new matching results are shown in column 3 of Table 7.5, already shown. Only those
variables with a potentially strong role in both employment and programme participation
are included in the probit. Labour market outcomes for programmes are most often based
on gender, age and unemployment experience which are included in the reduced model.
The human capital effects of education, represented by highest qualification, and work
experience are added. Marital status, children and partner’s labour market behaviour are
included as variables that usually influence labour supply. Health, ethnicity and location
are other factors commonly entered as constraints to labour supply or demand. The
variation by location (state) was found to strongly influence SYETP participation [see
section 2.2.6]. The rural/urban location is based on background prior to programme entry,
retained from the former specification, because it is highly related to location in 1984 and
later surveys. But this variable might act as a better instrument for the influences of
personal background on labour market behaviour because location for young people is
mostly due to parental choice. All of these variables form a subgroup of the fuller original
specification. Note that CEP referrals is not included. Only one variable that was
formerly statistically significant in the full model was excluded: nature of schooling
(private, government, overseas, Roman Catholic). All other variables excluded from the
reduced model were not statistically significant in the estimated probit.